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<a href="#nested-classes">Classes</a> &#124;
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<div class="title">tensorNet Class Reference<div class="ingroups"><a class="el" href="group__deepVision.html">DNN Vision Library (jetson-inference)</a> &raquo; <a class="el" href="group__tensorNet.html">tensorNet</a></div></div>  </div>
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<p>Abstract class for loading a tensor network with TensorRT.  
 <a href="classtensorNet.html#details">More...</a></p>

<p><code>#include &lt;<a class="el" href="tensorNet_8h_source.html">tensorNet.h</a>&gt;</code></p>
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Inheritance diagram for tensorNet:</div>
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Classes</h2></td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet_1_1Logger.html">Logger</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classtensorNet_1_1Logger.html" title="Logger class for GIE info/warning/errors. ">Logger</a> class for GIE info/warning/errors.  <a href="classtensorNet_1_1Logger.html#details">More...</a><br /></td></tr>
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<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">struct &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="structtensorNet_1_1outputLayer.html">outputLayer</a></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:"><td class="memItemLeft" align="right" valign="top">class &#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet_1_1Profiler.html">Profiler</a></td></tr>
<tr class="memdesc:"><td class="mdescLeft">&#160;</td><td class="mdescRight"><a class="el" href="classtensorNet_1_1Profiler.html" title="Profiler interface for measuring layer timings. ">Profiler</a> interface for measuring layer timings.  <a href="classtensorNet_1_1Profiler.html#details">More...</a><br /></td></tr>
<tr class="separator:"><td class="memSeparator" colspan="2">&#160;</td></tr>
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<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-methods"></a>
Public Member Functions</h2></td></tr>
<tr class="memitem:ad19aafbfa262f9b8ffb0bff561f4d7f7"><td class="memItemLeft" align="right" valign="top">virtual&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ad19aafbfa262f9b8ffb0bff561f4d7f7">~tensorNet</a> ()</td></tr>
<tr class="memdesc:ad19aafbfa262f9b8ffb0bff561f4d7f7"><td class="mdescLeft">&#160;</td><td class="mdescRight">Destory.  <a href="#ad19aafbfa262f9b8ffb0bff561f4d7f7">More...</a><br /></td></tr>
<tr class="separator:ad19aafbfa262f9b8ffb0bff561f4d7f7"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2e63d4670461814bd863ee0d9bd41526"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2e63d4670461814bd863ee0d9bd41526">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean=NULL, const char *input_blob=&quot;data&quot;, const char *output_blob=&quot;prob&quot;, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a2e63d4670461814bd863ee0d9bd41526"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance.  <a href="#a2e63d4670461814bd863ee0d9bd41526">More...</a><br /></td></tr>
<tr class="separator:a2e63d4670461814bd863ee0d9bd41526"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0a06ffd12b465f39160f4a6925cccd9f"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a0a06ffd12b465f39160f4a6925cccd9f">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean, const char *input_blob, const std::vector&lt; std::string &gt; &amp;output_blobs, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a0a06ffd12b465f39160f4a6925cccd9f"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance with multiple output layers.  <a href="#a0a06ffd12b465f39160f4a6925cccd9f">More...</a><br /></td></tr>
<tr class="separator:a0a06ffd12b465f39160f4a6925cccd9f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a168c7f75c9fd6d264afd016e144f3878"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a168c7f75c9fd6d264afd016e144f3878">LoadNetwork</a> (const char *prototxt, const char *model, const char *mean, const char *input_blob, const <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &amp;input_dims, const std::vector&lt; std::string &gt; &amp;output_blobs, uint32_t maxBatchSize=<a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a>, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision=<a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a>, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowGPUFallback=true, nvinfer1::IInt8Calibrator *calibrator=NULL, cudaStream_t stream=NULL)</td></tr>
<tr class="memdesc:a168c7f75c9fd6d264afd016e144f3878"><td class="mdescLeft">&#160;</td><td class="mdescRight">Load a new network instance (this variant is used for UFF models)  <a href="#a168c7f75c9fd6d264afd016e144f3878">More...</a><br /></td></tr>
<tr class="separator:a168c7f75c9fd6d264afd016e144f3878"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a3413eb0ad4f240f457f192f39e2e03e8"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a3413eb0ad4f240f457f192f39e2e03e8">EnableLayerProfiler</a> ()</td></tr>
<tr class="memdesc:a3413eb0ad4f240f457f192f39e2e03e8"><td class="mdescLeft">&#160;</td><td class="mdescRight">Manually enable layer profiling times.  <a href="#a3413eb0ad4f240f457f192f39e2e03e8">More...</a><br /></td></tr>
<tr class="separator:a3413eb0ad4f240f457f192f39e2e03e8"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae49f74ff83e46112a30318fa0576cace"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae49f74ff83e46112a30318fa0576cace">EnableDebug</a> ()</td></tr>
<tr class="memdesc:ae49f74ff83e46112a30318fa0576cace"><td class="mdescLeft">&#160;</td><td class="mdescRight">Manually enable debug messages and synchronization.  <a href="#ae49f74ff83e46112a30318fa0576cace">More...</a><br /></td></tr>
<tr class="separator:ae49f74ff83e46112a30318fa0576cace"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7d0ec0d8504ac8b26c5ab4a6136599ca"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7d0ec0d8504ac8b26c5ab4a6136599ca">AllowGPUFallback</a> () const</td></tr>
<tr class="memdesc:a7d0ec0d8504ac8b26c5ab4a6136599ca"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return true if GPU fallback is enabled.  <a href="#a7d0ec0d8504ac8b26c5ab4a6136599ca">More...</a><br /></td></tr>
<tr class="separator:a7d0ec0d8504ac8b26c5ab4a6136599ca"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a92bb737172d26bda5f67d15346a02514"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a92bb737172d26bda5f67d15346a02514">GetDevice</a> () const</td></tr>
<tr class="memdesc:a92bb737172d26bda5f67d15346a02514"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the device being used for execution.  <a href="#a92bb737172d26bda5f67d15346a02514">More...</a><br /></td></tr>
<tr class="separator:a92bb737172d26bda5f67d15346a02514"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afb38b5f171025e987a00214cc4379ca9"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#afb38b5f171025e987a00214cc4379ca9">GetPrecision</a> () const</td></tr>
<tr class="memdesc:afb38b5f171025e987a00214cc4379ca9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the type of precision being used.  <a href="#afb38b5f171025e987a00214cc4379ca9">More...</a><br /></td></tr>
<tr class="separator:afb38b5f171025e987a00214cc4379ca9"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a6b8e8dba05bc5c677027913d8c64f259"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a6b8e8dba05bc5c677027913d8c64f259">IsPrecision</a> (<a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type) const</td></tr>
<tr class="memdesc:a6b8e8dba05bc5c677027913d8c64f259"><td class="mdescLeft">&#160;</td><td class="mdescRight">Check if a particular precision is being used.  <a href="#a6b8e8dba05bc5c677027913d8c64f259">More...</a><br /></td></tr>
<tr class="separator:a6b8e8dba05bc5c677027913d8c64f259"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a34e350ec6185277ac09ae55a79403e62"><td class="memItemLeft" align="right" valign="top">cudaStream_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a34e350ec6185277ac09ae55a79403e62">GetStream</a> () const</td></tr>
<tr class="memdesc:a34e350ec6185277ac09ae55a79403e62"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the stream that the device is operating on.  <a href="#a34e350ec6185277ac09ae55a79403e62">More...</a><br /></td></tr>
<tr class="separator:a34e350ec6185277ac09ae55a79403e62"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a78cecfb7505be0ea59d29041abc85cbb"><td class="memItemLeft" align="right" valign="top">cudaStream_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a78cecfb7505be0ea59d29041abc85cbb">CreateStream</a> (bool nonBlocking=true)</td></tr>
<tr class="memdesc:a78cecfb7505be0ea59d29041abc85cbb"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create and use a new stream for execution.  <a href="#a78cecfb7505be0ea59d29041abc85cbb">More...</a><br /></td></tr>
<tr class="separator:a78cecfb7505be0ea59d29041abc85cbb"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a679b177784c85bfdba63dcd1008ff633"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a679b177784c85bfdba63dcd1008ff633">SetStream</a> (cudaStream_t stream)</td></tr>
<tr class="memdesc:a679b177784c85bfdba63dcd1008ff633"><td class="mdescLeft">&#160;</td><td class="mdescRight">Set the stream that the device is operating on.  <a href="#a679b177784c85bfdba63dcd1008ff633">More...</a><br /></td></tr>
<tr class="separator:a679b177784c85bfdba63dcd1008ff633"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a624881afe27acd2b2fff0f0f75308ea2"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a624881afe27acd2b2fff0f0f75308ea2">GetPrototxtPath</a> () const</td></tr>
<tr class="memdesc:a624881afe27acd2b2fff0f0f75308ea2"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the path to the network prototxt file.  <a href="#a624881afe27acd2b2fff0f0f75308ea2">More...</a><br /></td></tr>
<tr class="separator:a624881afe27acd2b2fff0f0f75308ea2"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac74d7f0571b7782b945ff85fd6894044"><td class="memItemLeft" align="right" valign="top">const char *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac74d7f0571b7782b945ff85fd6894044">GetModelPath</a> () const</td></tr>
<tr class="memdesc:ac74d7f0571b7782b945ff85fd6894044"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the path to the network model file.  <a href="#ac74d7f0571b7782b945ff85fd6894044">More...</a><br /></td></tr>
<tr class="separator:ac74d7f0571b7782b945ff85fd6894044"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:acfa7f1f01b46f658ffc96f8a002e8d48"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#acfa7f1f01b46f658ffc96f8a002e8d48">GetModelType</a> () const</td></tr>
<tr class="memdesc:acfa7f1f01b46f658ffc96f8a002e8d48"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the format of the network model.  <a href="#acfa7f1f01b46f658ffc96f8a002e8d48">More...</a><br /></td></tr>
<tr class="separator:acfa7f1f01b46f658ffc96f8a002e8d48"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a0a09d691ea080bd9734c5782c8fff6fd"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a0a09d691ea080bd9734c5782c8fff6fd">IsModelType</a> (<a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a> type) const</td></tr>
<tr class="memdesc:a0a09d691ea080bd9734c5782c8fff6fd"><td class="mdescLeft">&#160;</td><td class="mdescRight">Return true if the model is of the specified format.  <a href="#a0a09d691ea080bd9734c5782c8fff6fd">More...</a><br /></td></tr>
<tr class="separator:a0a09d691ea080bd9734c5782c8fff6fd"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a9dd2db089176ae6878e9ea7dd8fd80c3"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a9dd2db089176ae6878e9ea7dd8fd80c3">GetNetworkFPS</a> ()</td></tr>
<tr class="memdesc:a9dd2db089176ae6878e9ea7dd8fd80c3"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the network frames per second (FPS).  <a href="#a9dd2db089176ae6878e9ea7dd8fd80c3">More...</a><br /></td></tr>
<tr class="separator:a9dd2db089176ae6878e9ea7dd8fd80c3"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a49faef5920860345e503023b7c84423c"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a49faef5920860345e503023b7c84423c">GetNetworkTime</a> ()</td></tr>
<tr class="memdesc:a49faef5920860345e503023b7c84423c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the network runtime (in milliseconds).  <a href="#a49faef5920860345e503023b7c84423c">More...</a><br /></td></tr>
<tr class="separator:a49faef5920860345e503023b7c84423c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad266f93035a80dca80cd84d971e4f69b"><td class="memItemLeft" align="right" valign="top">float2&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ad266f93035a80dca80cd84d971e4f69b">GetProfilerTime</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ad266f93035a80dca80cd84d971e4f69b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the profiler runtime (in milliseconds).  <a href="#ad266f93035a80dca80cd84d971e4f69b">More...</a><br /></td></tr>
<tr class="separator:ad266f93035a80dca80cd84d971e4f69b"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a27cf81b3fecf93d2e63a61220a54b393"><td class="memItemLeft" align="right" valign="top">float&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a27cf81b3fecf93d2e63a61220a54b393">GetProfilerTime</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query, <a class="el" href="group__tensorNet.html#gaaa4127ed22c7165a32d0474ebf97975e">profilerDevice</a> device)</td></tr>
<tr class="memdesc:a27cf81b3fecf93d2e63a61220a54b393"><td class="mdescLeft">&#160;</td><td class="mdescRight">Retrieve the profiler runtime (in milliseconds).  <a href="#a27cf81b3fecf93d2e63a61220a54b393">More...</a><br /></td></tr>
<tr class="separator:a27cf81b3fecf93d2e63a61220a54b393"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:afc0f50abcf6ac71e96d51eba3ed53d4b"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#afc0f50abcf6ac71e96d51eba3ed53d4b">PrintProfilerTimes</a> ()</td></tr>
<tr class="memdesc:afc0f50abcf6ac71e96d51eba3ed53d4b"><td class="mdescLeft">&#160;</td><td class="mdescRight">Print the profiler times (in millseconds).  <a href="#afc0f50abcf6ac71e96d51eba3ed53d4b">More...</a><br /></td></tr>
<tr class="separator:afc0f50abcf6ac71e96d51eba3ed53d4b"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pub-static-methods"></a>
Static Public Member Functions</h2></td></tr>
<tr class="memitem:abe33fae5332296e2d917cb4ce435e255"><td class="memItemLeft" align="right" valign="top">static <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#abe33fae5332296e2d917cb4ce435e255">FindFastestPrecision</a> (<a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>, bool allowInt8=true)</td></tr>
<tr class="memdesc:abe33fae5332296e2d917cb4ce435e255"><td class="mdescLeft">&#160;</td><td class="mdescRight">Determine the fastest native precision on a device.  <a href="#abe33fae5332296e2d917cb4ce435e255">More...</a><br /></td></tr>
<tr class="separator:abe33fae5332296e2d917cb4ce435e255"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae88436e652afdd7bceef7cb7c5fde7a6"><td class="memItemLeft" align="right" valign="top">static std::vector&lt; <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae88436e652afdd7bceef7cb7c5fde7a6">DetectNativePrecisions</a> (<a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>)</td></tr>
<tr class="memdesc:ae88436e652afdd7bceef7cb7c5fde7a6"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect the precisions supported natively on a device.  <a href="#ae88436e652afdd7bceef7cb7c5fde7a6">More...</a><br /></td></tr>
<tr class="separator:ae88436e652afdd7bceef7cb7c5fde7a6"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aa3bf1a3bf1fca38b39a200b4d8f727b2"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aa3bf1a3bf1fca38b39a200b4d8f727b2">DetectNativePrecision</a> (const std::vector&lt; <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> &gt; &amp;nativeTypes, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> type)</td></tr>
<tr class="memdesc:aa3bf1a3bf1fca38b39a200b4d8f727b2"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect if a particular precision is supported natively.  <a href="#aa3bf1a3bf1fca38b39a200b4d8f727b2">More...</a><br /></td></tr>
<tr class="separator:aa3bf1a3bf1fca38b39a200b4d8f727b2"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7d72ec8bbaf61278ce533afd60d5391c"><td class="memItemLeft" align="right" valign="top">static bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7d72ec8bbaf61278ce533afd60d5391c">DetectNativePrecision</a> (<a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device=<a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a>)</td></tr>
<tr class="memdesc:a7d72ec8bbaf61278ce533afd60d5391c"><td class="mdescLeft">&#160;</td><td class="mdescRight">Detect if a particular precision is supported natively.  <a href="#a7d72ec8bbaf61278ce533afd60d5391c">More...</a><br /></td></tr>
<tr class="separator:a7d72ec8bbaf61278ce533afd60d5391c"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-methods"></a>
Protected Member Functions</h2></td></tr>
<tr class="memitem:ab6e617d96e5542bef023ee9d4c96388a"><td class="memItemLeft" align="right" valign="top">&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ab6e617d96e5542bef023ee9d4c96388a">tensorNet</a> ()</td></tr>
<tr class="memdesc:ab6e617d96e5542bef023ee9d4c96388a"><td class="mdescLeft">&#160;</td><td class="mdescRight">Constructor.  <a href="#ab6e617d96e5542bef023ee9d4c96388a">More...</a><br /></td></tr>
<tr class="separator:ab6e617d96e5542bef023ee9d4c96388a"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a081b95210634e8ddb21e99d9ad1aa497"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a081b95210634e8ddb21e99d9ad1aa497">ProfileModel</a> (const std::string &amp;deployFile, const std::string &amp;modelFile, const char *input, const <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &amp;inputDims, const std::vector&lt; std::string &gt; &amp;outputs, uint32_t maxBatchSize, <a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a> precision, <a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a> device, bool allowGPUFallback, nvinfer1::IInt8Calibrator *calibrator, std::ostream &amp;modelStream)</td></tr>
<tr class="memdesc:a081b95210634e8ddb21e99d9ad1aa497"><td class="mdescLeft">&#160;</td><td class="mdescRight">Create and output an optimized network model.  <a href="#a081b95210634e8ddb21e99d9ad1aa497">More...</a><br /></td></tr>
<tr class="separator:a081b95210634e8ddb21e99d9ad1aa497"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a088c3bf591e45e52ec227491f6f299ad"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a088c3bf591e45e52ec227491f6f299ad">PROFILER_BEGIN</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:a088c3bf591e45e52ec227491f6f299ad"><td class="mdescLeft">&#160;</td><td class="mdescRight">Begin a profiling query, before network is run.  <a href="#a088c3bf591e45e52ec227491f6f299ad">More...</a><br /></td></tr>
<tr class="separator:a088c3bf591e45e52ec227491f6f299ad"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac8582b9a6099e3265da4c3f9fdf804ea"><td class="memItemLeft" align="right" valign="top">void&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac8582b9a6099e3265da4c3f9fdf804ea">PROFILER_END</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ac8582b9a6099e3265da4c3f9fdf804ea"><td class="mdescLeft">&#160;</td><td class="mdescRight">End a profiling query, after the network is run.  <a href="#ac8582b9a6099e3265da4c3f9fdf804ea">More...</a><br /></td></tr>
<tr class="separator:ac8582b9a6099e3265da4c3f9fdf804ea"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae2e0ae17baf6e1975aaad7a7f5c60ce9"><td class="memItemLeft" align="right" valign="top">bool&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae2e0ae17baf6e1975aaad7a7f5c60ce9">PROFILER_QUERY</a> (<a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a> query)</td></tr>
<tr class="memdesc:ae2e0ae17baf6e1975aaad7a7f5c60ce9"><td class="mdescLeft">&#160;</td><td class="mdescRight">Query the CUDA part of a profiler query.  <a href="#ae2e0ae17baf6e1975aaad7a7f5c60ce9">More...</a><br /></td></tr>
<tr class="separator:ae2e0ae17baf6e1975aaad7a7f5c60ce9"><td class="memSeparator" colspan="2">&#160;</td></tr>
</table><table class="memberdecls">
<tr class="heading"><td colspan="2"><h2 class="groupheader"><a name="pro-attribs"></a>
Protected Attributes</h2></td></tr>
<tr class="memitem:a6bd429ccb1dc3717b2a4a5ad8e555cd0"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtensorNet_1_1Logger.html">tensorNet::Logger</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a6bd429ccb1dc3717b2a4a5ad8e555cd0">gLogger</a></td></tr>
<tr class="separator:a6bd429ccb1dc3717b2a4a5ad8e555cd0"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ae1f74819d644d0f289253fbcf5d0655f"><td class="memItemLeft" align="right" valign="top"><a class="el" href="classtensorNet_1_1Profiler.html">tensorNet::Profiler</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ae1f74819d644d0f289253fbcf5d0655f">gProfiler</a></td></tr>
<tr class="separator:ae1f74819d644d0f289253fbcf5d0655f"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a54005b86b851fa71aeb7a83d4ad32362"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a54005b86b851fa71aeb7a83d4ad32362">mPrototxtPath</a></td></tr>
<tr class="separator:a54005b86b851fa71aeb7a83d4ad32362"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a7cb91e06b296431680d20e7e9fb0187d"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a7cb91e06b296431680d20e7e9fb0187d">mModelPath</a></td></tr>
<tr class="separator:a7cb91e06b296431680d20e7e9fb0187d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a11eeaa1e454a97a5634c7fb5ea1bc23d"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a11eeaa1e454a97a5634c7fb5ea1bc23d">mMeanPath</a></td></tr>
<tr class="separator:a11eeaa1e454a97a5634c7fb5ea1bc23d"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ac040cf851463cd595a20a9400a5833c2"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ac040cf851463cd595a20a9400a5833c2">mInputBlobName</a></td></tr>
<tr class="separator:ac040cf851463cd595a20a9400a5833c2"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aaa9ac0fae88a426f1a5325886da3b009"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aaa9ac0fae88a426f1a5325886da3b009">mCacheEnginePath</a></td></tr>
<tr class="separator:aaa9ac0fae88a426f1a5325886da3b009"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a64fccb1894b0926e54a18fa47a271c70"><td class="memItemLeft" align="right" valign="top">std::string&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a64fccb1894b0926e54a18fa47a271c70">mCacheCalibrationPath</a></td></tr>
<tr class="separator:a64fccb1894b0926e54a18fa47a271c70"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2f14a2f4a4dfbb51b80f80a2e47a695c"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2f14a2f4a4dfbb51b80f80a2e47a695c">mDevice</a></td></tr>
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<tr class="memitem:a164c1dcf9dcbc085c1b421855eda665f"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a164c1dcf9dcbc085c1b421855eda665f">mPrecision</a></td></tr>
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<tr class="memitem:ab5c88cf4590b53804ebedaa292d1402c"><td class="memItemLeft" align="right" valign="top"><a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a>&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ab5c88cf4590b53804ebedaa292d1402c">mModelType</a></td></tr>
<tr class="separator:ab5c88cf4590b53804ebedaa292d1402c"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a1ed6e418a135650c7cf91498379727ae"><td class="memItemLeft" align="right" valign="top">cudaStream_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a1ed6e418a135650c7cf91498379727ae">mStream</a></td></tr>
<tr class="separator:a1ed6e418a135650c7cf91498379727ae"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:aac52fdcc0579c0426e21141636349dea"><td class="memItemLeft" align="right" valign="top">cudaEvent_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#aac52fdcc0579c0426e21141636349dea">mEventsGPU</a> [<a class="el" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a> *2]</td></tr>
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<tr class="memitem:af4cb4b37a74806164257e9529cb8ed70"><td class="memItemLeft" align="right" valign="top">timespec&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#af4cb4b37a74806164257e9529cb8ed70">mEventsCPU</a> [<a class="el" href="group__tensorNet.html#ggae34d45c0faa674ef4cc0fbfc8fae5809af9132edd0371e716aed4d46e3da5e9ea">PROFILER_TOTAL</a> *2]</td></tr>
<tr class="separator:af4cb4b37a74806164257e9529cb8ed70"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a275ce2318a63dcaafc1e0120a53fe606"><td class="memItemLeft" align="right" valign="top">nvinfer1::IRuntime *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a275ce2318a63dcaafc1e0120a53fe606">mInfer</a></td></tr>
<tr class="separator:a275ce2318a63dcaafc1e0120a53fe606"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:ad6d2272a2560bec119fa570438e3eb19"><td class="memItemLeft" align="right" valign="top">nvinfer1::ICudaEngine *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#ad6d2272a2560bec119fa570438e3eb19">mEngine</a></td></tr>
<tr class="separator:ad6d2272a2560bec119fa570438e3eb19"><td class="memSeparator" colspan="2">&#160;</td></tr>
<tr class="memitem:a2c745474e60145ee826b53e294e7f478"><td class="memItemLeft" align="right" valign="top">nvinfer1::IExecutionContext *&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a2c745474e60145ee826b53e294e7f478">mContext</a></td></tr>
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<tr class="memitem:accab52fa354232149048440da0071573"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#accab52fa354232149048440da0071573">mWidth</a></td></tr>
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<tr class="memitem:abc0c2b349cb27ddf6e42f668fa582a34"><td class="memItemLeft" align="right" valign="top">uint32_t&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#abc0c2b349cb27ddf6e42f668fa582a34">mHeight</a></td></tr>
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<tr class="memitem:a3487d6af48f91afcbeea76552d21d1c5"><td class="memItemLeft" align="right" valign="top">std::vector&lt; <a class="el" href="structtensorNet_1_1outputLayer.html">outputLayer</a> &gt;&#160;</td><td class="memItemRight" valign="bottom"><a class="el" href="classtensorNet.html#a3487d6af48f91afcbeea76552d21d1c5">mOutputs</a></td></tr>
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<a name="details" id="details"></a><h2 class="groupheader">Detailed Description</h2>
<div class="textblock"><p>Abstract class for loading a tensor network with TensorRT. </p>
<p>For example implementations, </p><dl class="section see"><dt>See also</dt><dd><a class="el" href="classimageNet.html" title="Image recognition with classification networks, using TensorRT. ">imageNet</a> and </dd>
<dd>
<a class="el" href="classdetectNet.html" title="Object recognition and localization networks with TensorRT support. ">detectNet</a> </dd></dl>
</div><h2 class="groupheader">Constructor &amp; Destructor Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#ad19aafbfa262f9b8ffb0bff561f4d7f7">&#9670;&nbsp;</a></span>~tensorNet()</h2>

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<p>Destory. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#ab6e617d96e5542bef023ee9d4c96388a">&#9670;&nbsp;</a></span>tensorNet()</h2>

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<p>Constructor. </p>

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<h2 class="groupheader">Member Function Documentation</h2>
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<h2 class="memtitle"><span class="permalink"><a href="#a7d0ec0d8504ac8b26c5ab4a6136599ca">&#9670;&nbsp;</a></span>AllowGPUFallback()</h2>

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<p>Return true if GPU fallback is enabled. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a78cecfb7505be0ea59d29041abc85cbb">&#9670;&nbsp;</a></span>CreateStream()</h2>

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<p>Create and use a new stream for execution. </p>

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<p>Detect if a particular precision is supported natively. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a7d72ec8bbaf61278ce533afd60d5391c">&#9670;&nbsp;</a></span>DetectNativePrecision() <span class="overload">[2/2]</span></h2>

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          <td class="paramname"><em>device</em> = <code><a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></code>&#160;</td>
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<p>Detect if a particular precision is supported natively. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#ae88436e652afdd7bceef7cb7c5fde7a6">&#9670;&nbsp;</a></span>DetectNativePrecisions()</h2>

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<p>Detect the precisions supported natively on a device. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#ae49f74ff83e46112a30318fa0576cace">&#9670;&nbsp;</a></span>EnableDebug()</h2>

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<p>Manually enable debug messages and synchronization. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a3413eb0ad4f240f457f192f39e2e03e8">&#9670;&nbsp;</a></span>EnableLayerProfiler()</h2>

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<p>Manually enable layer profiling times. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#abe33fae5332296e2d917cb4ce435e255">&#9670;&nbsp;</a></span>FindFastestPrecision()</h2>

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<p>Determine the fastest native precision on a device. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a92bb737172d26bda5f67d15346a02514">&#9670;&nbsp;</a></span>GetDevice()</h2>

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<p>Retrieve the device being used for execution. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#ac74d7f0571b7782b945ff85fd6894044">&#9670;&nbsp;</a></span>GetModelPath()</h2>

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<p>Retrieve the path to the network model file. </p>

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<p>Retrieve the format of the network model. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a9dd2db089176ae6878e9ea7dd8fd80c3">&#9670;&nbsp;</a></span>GetNetworkFPS()</h2>

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<p>Retrieve the network frames per second (FPS). </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a49faef5920860345e503023b7c84423c">&#9670;&nbsp;</a></span>GetNetworkTime()</h2>

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<p>Retrieve the network runtime (in milliseconds). </p>

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<h2 class="memtitle"><span class="permalink"><a href="#afb38b5f171025e987a00214cc4379ca9">&#9670;&nbsp;</a></span>GetPrecision()</h2>

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<p>Retrieve the type of precision being used. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#ad266f93035a80dca80cd84d971e4f69b">&#9670;&nbsp;</a></span>GetProfilerTime() <span class="overload">[1/2]</span></h2>

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          <td class="memname">float2 tensorNet::GetProfilerTime </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a>&#160;</td>
          <td class="paramname"><em>query</em></td><td>)</td>
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<p>Retrieve the profiler runtime (in milliseconds). </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a27cf81b3fecf93d2e63a61220a54b393">&#9670;&nbsp;</a></span>GetProfilerTime() <span class="overload">[2/2]</span></h2>

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          <td class="memname">float tensorNet::GetProfilerTime </td>
          <td>(</td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gae34d45c0faa674ef4cc0fbfc8fae5809">profilerQuery</a>&#160;</td>
          <td class="paramname"><em>query</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaaa4127ed22c7165a32d0474ebf97975e">profilerDevice</a>&#160;</td>
          <td class="paramname"><em>device</em>&#160;</td>
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          <td>)</td>
          <td></td><td></td>
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<p>Retrieve the profiler runtime (in milliseconds). </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a624881afe27acd2b2fff0f0f75308ea2">&#9670;&nbsp;</a></span>GetPrototxtPath()</h2>

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          <td class="paramname"></td><td>)</td>
          <td> const</td>
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<p>Retrieve the path to the network prototxt file. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a34e350ec6185277ac09ae55a79403e62">&#9670;&nbsp;</a></span>GetStream()</h2>

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<p>Retrieve the stream that the device is operating on. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a0a09d691ea080bd9734c5782c8fff6fd">&#9670;&nbsp;</a></span>IsModelType()</h2>

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          <td>(</td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#ga5d4597e0e7beae7133d542e220528725">modelType</a>&#160;</td>
          <td class="paramname"><em>type</em></td><td>)</td>
          <td> const</td>
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<p>Return true if the model is of the specified format. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a6b8e8dba05bc5c677027913d8c64f259">&#9670;&nbsp;</a></span>IsPrecision()</h2>

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          <td>(</td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>type</em></td><td>)</td>
          <td> const</td>
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<p>Check if a particular precision is being used. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a2e63d4670461814bd863ee0d9bd41526">&#9670;&nbsp;</a></span>LoadNetwork() <span class="overload">[1/3]</span></h2>

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          <td class="memname">bool tensorNet::LoadNetwork </td>
          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>prototxt</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>model</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>mean</em> = <code>NULL</code>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>input_blob</em> = <code>&quot;data&quot;</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>output_blob</em> = <code>&quot;prob&quot;</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em> = <code><a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></code>, </td>
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          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em> = <code><a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></code>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em> = <code><a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></code>, </td>
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          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em> = <code>true</code>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">nvinfer1::IInt8Calibrator *&#160;</td>
          <td class="paramname"><em>calibrator</em> = <code>NULL</code>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">cudaStream_t&#160;</td>
          <td class="paramname"><em>stream</em> = <code>NULL</code>&#160;</td>
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          <td></td>
          <td>)</td>
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<p>Load a new network instance. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">prototxt</td><td>File path to the deployable network prototxt </td></tr>
    <tr><td class="paramname">model</td><td>File path to the caffemodel </td></tr>
    <tr><td class="paramname">mean</td><td>File path to the mean value binary proto (NULL if none) </td></tr>
    <tr><td class="paramname">input_blob</td><td>The name of the input blob data to the network. </td></tr>
    <tr><td class="paramname">output_blob</td><td>The name of the output blob data from the network. </td></tr>
    <tr><td class="paramname">maxBatchSize</td><td>The maximum batch size that the network will be optimized for. </td></tr>
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  </dd>
</dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a0a06ffd12b465f39160f4a6925cccd9f">&#9670;&nbsp;</a></span>LoadNetwork() <span class="overload">[2/3]</span></h2>

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          <td class="memname">bool tensorNet::LoadNetwork </td>
          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>prototxt</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>model</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>mean</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>input_blob</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const std::vector&lt; std::string &gt; &amp;&#160;</td>
          <td class="paramname"><em>output_blobs</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em> = <code><a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em> = <code><a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em> = <code><a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></code>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em> = <code>true</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">nvinfer1::IInt8Calibrator *&#160;</td>
          <td class="paramname"><em>calibrator</em> = <code>NULL</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">cudaStream_t&#160;</td>
          <td class="paramname"><em>stream</em> = <code>NULL</code>&#160;</td>
        </tr>
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          <td></td>
          <td>)</td>
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<p>Load a new network instance with multiple output layers. </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">prototxt</td><td>File path to the deployable network prototxt </td></tr>
    <tr><td class="paramname">model</td><td>File path to the caffemodel </td></tr>
    <tr><td class="paramname">mean</td><td>File path to the mean value binary proto (NULL if none) </td></tr>
    <tr><td class="paramname">input_blob</td><td>The name of the input blob data to the network. </td></tr>
    <tr><td class="paramname">output_blobs</td><td>List of names of the output blobs from the network. </td></tr>
    <tr><td class="paramname">maxBatchSize</td><td>The maximum batch size that the network will be optimized for. </td></tr>
  </table>
  </dd>
</dl>

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<h2 class="memtitle"><span class="permalink"><a href="#a168c7f75c9fd6d264afd016e144f3878">&#9670;&nbsp;</a></span>LoadNetwork() <span class="overload">[3/3]</span></h2>

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          <td>(</td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>prototxt</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>model</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>mean</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>input_blob</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &amp;&#160;</td>
          <td class="paramname"><em>input_dims</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const std::vector&lt; std::string &gt; &amp;&#160;</td>
          <td class="paramname"><em>output_blobs</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em> = <code><a class="el" href="group__tensorNet.html#ga5a46a965749d6118e01307fd4d4865c9">DEFAULT_MAX_BATCH_SIZE</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaac6604fd52c6e5db82877390e0378623">precisionType</a>&#160;</td>
          <td class="paramname"><em>precision</em> = <code><a class="el" href="group__tensorNet.html#ggaac6604fd52c6e5db82877390e0378623a1d325738f49e8e4c424ff671624e66f9">TYPE_FASTEST</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype"><a class="el" href="group__tensorNet.html#gaa5d3f9981cdbd91516c1474006a80fe4">deviceType</a>&#160;</td>
          <td class="paramname"><em>device</em> = <code><a class="el" href="group__tensorNet.html#ggaa5d3f9981cdbd91516c1474006a80fe4adc7f3f88455afa81458863e5b3092e4b">DEVICE_GPU</a></code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">bool&#160;</td>
          <td class="paramname"><em>allowGPUFallback</em> = <code>true</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">nvinfer1::IInt8Calibrator *&#160;</td>
          <td class="paramname"><em>calibrator</em> = <code>NULL</code>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">cudaStream_t&#160;</td>
          <td class="paramname"><em>stream</em> = <code>NULL</code>&#160;</td>
        </tr>
        <tr>
          <td></td>
          <td>)</td>
          <td></td><td></td>
        </tr>
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</div><div class="memdoc">

<p>Load a new network instance (this variant is used for UFF models) </p>
<dl class="params"><dt>Parameters</dt><dd>
  <table class="params">
    <tr><td class="paramname">prototxt</td><td>File path to the deployable network prototxt </td></tr>
    <tr><td class="paramname">model</td><td>File path to the caffemodel </td></tr>
    <tr><td class="paramname">mean</td><td>File path to the mean value binary proto (NULL if none) </td></tr>
    <tr><td class="paramname">input_blob</td><td>The name of the input blob data to the network. </td></tr>
    <tr><td class="paramname">input_dims</td><td>The dimensions of the input blob (used for UFF). </td></tr>
    <tr><td class="paramname">output_blobs</td><td>List of names of the output blobs from the network. </td></tr>
    <tr><td class="paramname">maxBatchSize</td><td>The maximum batch size that the network will be optimized for. </td></tr>
  </table>
  </dd>
</dl>

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<h2 class="memtitle"><span class="permalink"><a href="#afc0f50abcf6ac71e96d51eba3ed53d4b">&#9670;&nbsp;</a></span>PrintProfilerTimes()</h2>

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<p>Print the profiler times (in millseconds). </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a081b95210634e8ddb21e99d9ad1aa497">&#9670;&nbsp;</a></span>ProfileModel()</h2>

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          <td class="paramtype">const std::string &amp;&#160;</td>
          <td class="paramname"><em>deployFile</em>, </td>
        </tr>
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          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const std::string &amp;&#160;</td>
          <td class="paramname"><em>modelFile</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const char *&#160;</td>
          <td class="paramname"><em>input</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const <a class="el" href="tensorNet_8h.html#a64c8f3dfeacfa962ff9e23c586aedd1b">Dims3</a> &amp;&#160;</td>
          <td class="paramname"><em>inputDims</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">const std::vector&lt; std::string &gt; &amp;&#160;</td>
          <td class="paramname"><em>outputs</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
          <td class="paramtype">uint32_t&#160;</td>
          <td class="paramname"><em>maxBatchSize</em>, </td>
        </tr>
        <tr>
          <td class="paramkey"></td>
          <td></td>
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<p>Create and output an optimized network model. </p>
<dl class="section note"><dt>Note</dt><dd>this function is automatically used by LoadNetwork, but also can be used individually to perform the network operations offline. </dd></dl>
<dl class="params"><dt>Parameters</dt><dd>
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<h2 class="memtitle"><span class="permalink"><a href="#a088c3bf591e45e52ec227491f6f299ad">&#9670;&nbsp;</a></span>PROFILER_BEGIN()</h2>

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<p>Begin a profiling query, before network is run. </p>

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<p>End a profiling query, after the network is run. </p>

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<p>Query the CUDA part of a profiler query. </p>

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<p>Set the stream that the device is operating on. </p>

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<h2 class="memtitle"><span class="permalink"><a href="#a3487d6af48f91afcbeea76552d21d1c5">&#9670;&nbsp;</a></span>mOutputs</h2>

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<h2 class="memtitle"><span class="permalink"><a href="#a545348243b65ce04047fd10d47e1716c">&#9670;&nbsp;</a></span>mProfilerQueriesUsed</h2>

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<h2 class="memtitle"><span class="permalink"><a href="#a1ed6e418a135650c7cf91498379727ae">&#9670;&nbsp;</a></span>mStream</h2>

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<hr/>The documentation for this class was generated from the following file:<ul>
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